A general class of sliding surface for sliding mode control

In the conventional sliding mode control, the relative degree of the chosen sliding surface is usually one. This paper addresses a general class of sliding surface whose relative degree is no longer restricted to one. We show that when the relative degree is more than two, it is inevitable that there will exist a limit cycle for the nonlinear sign function. And for the case of relative degree two the system possesses poor phase margin. However, these disadvantages can be remedied remarkably by smoothing out the control nonlinearity in a suitable boundary layer with a saturation function that ensures asymptotic stability of the overall system     

Coefficients of dynamic friction and the mechanical melting mechanism for vinylidene chloride copolymers

Previous research and this research indicate that the mechanical melting for poly(vinylidene chloride) copolymers (PVDC) is complex. Mechanical melting is defined as the melting (or devitrification) of a polymer when a significant portion of the thermal energy originates from a mechanical energy dissipative process. PVDC mechanically melted on a moving metal surface at temperatures of the test instrument that were considerably lower than the differential scanning calorimetry (DSC) onset melting temperature. PVDC formulated with low levels of high density polyethylene (HDPE), however, melted at metal temperatures near the DSC onset melting temperature. Two different mechanical melting mechanisms are proposed to explan the data, and the frictional data are discussed with respect to solids conveying in a single-screw, plasticating extruder.     

Psychrotrophic violacein-producing bacteria isolated from Lake Winnipeg,Canada

Violet and purple bacterial pigmentations are uncommon when considering strict aerobes. Here we report discovery of two novel isolates, P102 and P117 from the freshwater Lake Winnipeg, each with violet to deep purple colony colouration. The relationship between pigment production and growth was investigated under different conditions, including a variety of carbon sources, pH, and temperatures. The violet compounds were purified using polar organic solvents, and then structurally characterized via mass spectrometry and nuclear magnetic resonance to be violacein and deoxyviolacein. Strain P117 produced higher concentrations of the darker pigment deoxyviolacein, which resulted in a deeper hue of violet than in cultures of P102. Strain P102, synthesized violacein maximally in liquid rich organic medium at pH 8 and 20 °C, and had 99.3% sequence similarity to the 16S rDNA from Janthinobacterium lividum. Strain P117, related to Massilia violaceinigra sharing 99.2% 16S rDNA sequence similarity, also produced violacein at similar optimal conditions, but developed higher concentrations of pigment at 15 °C. Culture-based methods found that violacein producers composed 0.001% or 0.023% CFU of environmental heterotrophic populations using BG-11 and potato-based media, respectively. Culture-independent high-throughput ribosomal 16S V4 sequencing of environmental DNA was used to detect Gram-negative species known for their production of violacein. Of all bacterial and archaeal sequences present during the fall in littoral waters and sediment of Lake Winnipeg, 5.5% and 6.3%, respectively, belonged to species that have similar pigment, demonstrating the scarcity of violacein producers in this aquatic freshwater system.     

Bias-free identification of a linear model-predictive steering controller from measured driver steering behavior

Recent developments in modeling driver steering control with preview are reviewed. While some validation with experimental data has been presented, the rigorous application of formal system identification methods has not yet been attempted. This paper describes a steering controller based on linear model-predictive control. An indirect identification method that minimizes steering angle prediction error is developed. Special attention is given to filtering the prediction error so as to avoid identification bias that arises from the closed-loop operation of the driver-vehicle system. The identification procedure is applied to data collected from 14 test drivers performing double lane change maneuvers in an instrumented vehicle. It is found that the identification procedure successfully finds parameter values for the model that give small prediction errors. The procedure is also able to distinguish between the different steering strategies adopted by the test drivers.     

A critical review of the most popular types of neuro control

In this review article, the most popular types of neural network control systems are briefly introduced and their main features are reviewed. Neuro control systems are defined as control systems in which at least one artificial neural network (ANN) is directly involved in generating the control command. Initially, neural networks were mostly used to model system dynamics inversely to produce a control command which pushes the system towards a desired or reference value of the output (1989). At the next stage, neural networks were trained to track a reference model, and ANN model reference control appeared (1990). In that method, ANNs were used to extend the application of adaptive reference model control, which was a well‐known control technique. This attitude towards the extension of the application of well‐known control methods using ANNs was followed by the development of ANN model‐predictive (1991), ANN sliding mode (1994) and ANN feedback linearization (1995) techniques. As the first category of neuro controllers, inverse dynamics ANN controllers were frequently used to form a control system together with other controllers, but this attitude faded as other types of ANN control systems were developed. However, recently, this approach has been revived. In the last decade, control system designers started to use ANNs to compensate/cancel undesired or uncertain parts of systems' dynamics to facilitate the use of well‐known conventional control systems. The resultant control system usually includes two or three controllers. In this paper, applications of different ANN control systems are also addressed. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Energy and spectral dynamics in decaying compressible turbulence

The statistical properties of decaying compressible turbulence are investigated by direct numerical simulations of flow in a periodic cube. Starting with fully developed turbulence for various microscale Reynolds numbersR , rms Mach numbersM, and small- and large-scale compressive ratiosr _CS andr _CL , we find that the kinetic energy exhibits an exponential decay in time. Interactions between the compressive and rotational components of kinetic energy are weaker than self-interactions of the respective components. The energy spectrum of rotational component obeys the same Kolmogorov similarity law as for incompressible turbulence and forced compressible turbulence. The form of the energy spectrum of the compressive component, on the other hand, depends strongly onM. As the turbulence decays freely,R andM decrease in time butr _CS andr _CL tend to some universal values.     

A model for the compressive buckling of extended chain polymers

A model for the compressive buckling of an extended polymer chain is presented. The application of classical elastic instability analysis to an idealized polymer chain reveals that the bending rigidity and critical buckling loads for a chain are proportional to the force constants for valence bond angle bending and torsion. Highly oriented polymer fibres are treated as a collection of elastic chains that interact laterally. The critical stresses to buckle this collection of chains are calculated following a procedure developed to predict the compressive strengths of fibre-reinforced composites. This buckling stress is predicted to be equal to the shear modulus of the fibres and is the limiting value of compressive strength. Comparison of experimental and predicted values shows that the theory overestimates the compressive strength, but that there is a correlation of shear modulus with axial compressive strength. Consideration of flaws in both the theory and the material indicate that the compressive strength should be proportional to either the shear modulus or shear strength of the fibres.Nomenclature P axial compressive load (force) - P _cr critical buckling load (force) - M,M _i bending moments - l length of a link - p number of links - k elastic hinge constant - , _i angular rotation of hinges - L overall chain or column length - v,v _i lateral deflection of buckled chain or column - x, y, z Cartesian coordinate axes - E Young's modulus of isotropic column - I moment of inertia - a _ij matrix coefficients - A _p coefficient for exact buckling loads of chains - T energy change due to work of external load on buckled column or chain - U ₁ bending strain energy change of buckled column or chain - U ₂, U ₂ ^e , U ₂ ^s strain energy changes in elastic foundation, where e refers to extension mode buckling and s refers to shear mode buckling - E _t transverse modulus - G longitudinal shear modulus - b dimension associated with chain packing - A cross-sectional area per chain (=b ²) - f(x) curve fitted to shape of buckled chain - m,n,r integers - a _n coefficients of trigonometric series - _y normal strain iny-direction - _y normal stress iny-direction - xy shear strain inxy plane - xy shear stress inxy plane - u _x displacement inx-direction - u _y displacement iny-direction - V volume     

A new resolution criterion based on spectral signal-to-noise ratios

A new criterion for the "useful" resolution of electron micrographs of macromolecular particles is introduced. This criterion is based on estimation of the spatial frequency limit beyond which the spectral signal-to-noise ratio (SSNR) falls below an acceptable baseline. Applicable to both periodic and aperiodic specimens, this approach is particularly apposite for sets of correlation-averaged images. It represents a straightforward and intuitively appealing generalization of the traditional method of estimating the resolution of crystalline specimens from the spectral ranges of periodic reflections in their diffraction patterns. This method allows one to assess how closely the resolution of an averaged image based on N individual images approaches the ultimate resolution obtainable from an indefinitely large number of statistically equivalent images. Inter-relationships between the SSNR and two other measures of resolution, the differential phase residual and the Fourier ring correlation coefficient, are discussed, and their properties compared.